Introduces fundamental principles of artificial intelligence, including heuristic search, automated reasoning, handling uncertainty, and machine learning. Presents applications of AI techniques to real-world problems such as understanding the web, computer games, biomedical research, and assistive systems. This course is a prerequisite for advanced AI courses.
Julian Herwitz <julian dot herwitz at rochester dot edu>
Donato Borrello <donato dot borrello at rochester dot edu>
Detailed syllabus (subject to change)
Grade in the course will be calculated as follows:
Your letter grade will follow the University of Rochester Grading Scheme. The following table is an estimate of how the numeric grades will map onto the letter grades:
|C||Minimum Satisfactory Grade||≥60%|
|D||Minimum Passing Grade||≥50%|
Note that the University scheme puts
average somewhere between
C and B. This mapping from numbers to letters is subject to change,
but you get the idea: Getting an A requires truly
work. Even a B is
above average. Mind you, as
in Lake Wobegon, I'm
sure all CSC242 students are above average.
FYI: This information was presented in the first lecture, with a slight adjustment to accommodate quizzes.
Last update: Wednesday, 28-Mar-2012 11:36:44 EDT